Milk Quality Improvement Program, Department of Food Science, Cornell University, Ithaca, NY 14853.
Milk Quality Improvement Program, Department of Food Science, Cornell University, Ithaca, NY 14853.
J Dairy Sci. 2020 Jul;103(7):6716-6726. doi: 10.3168/jds.2019-17336. Epub 2020 Apr 22.
The sensory quality of fluid milk is of great importance to processors and consumers. Defects in the expected odor, flavor, or body of the product can affect consumer attitudes toward the product and, ultimately, willingness to purchase the product. Although many methods of sensory evaluation have been developed, defect judging is one particular method that has been used for decades in the dairy industry for evaluating fluid milk. Defect judging is a technique whereby panelists are trained to recognize and rate a standard set of fluid milk defects that originate from various sources (e.g., microbial spoilage). This technique is primarily used in processing facilities where identification of sensory defects can alert personnel to potential quality control issues in raw material quality, processing, or good manufacturing practices. In 2014-2016, a preliminary study of defective milk judging screening and training was conducted by the Milk Quality Improvement Program at Cornell University (Ithaca, NY). The study, which included 37 staff and students from the Cornell community, used prescreenings for common odors and basic tastes, followed by uniform training to select, initially train, and retrain defect judges of unflavored high temperature, short time fluid milk. Significant improvements were seen in correct identification of defect attributes following initial training for all defect attributes, with the exception of fruity/fermented. However, following retraining, significant improvements were observed in only 2 defect attributes: cooked and milk carton. These results demonstrate that initial training is important for panelists to correctly identify fluid milk defect attributes, but that subsequent retraining should be tailored toward specific attributes. This study provides a resource for dairy industry stakeholders to use to develop relevant and efficient training methods for fluid milk defect judging panels.
液态奶的感官质量对加工商和消费者都非常重要。产品在预期气味、风味或口感方面的缺陷会影响消费者对产品的态度，并最终影响他们购买产品的意愿。尽管已经开发出许多感官评估方法，但缺陷判断是乳制品行业几十年来用于评估液态奶的一种特殊方法。缺陷判断是一种技术，通过该技术，小组人员经过培训能够识别和评估源自各种来源（例如微生物腐败）的标准集液态奶缺陷。该技术主要用于加工设施中，在这些设施中，感官缺陷的识别可以提醒人员注意原材料质量、加工或良好生产规范方面的潜在质量控制问题。2014-2016 年，康奈尔大学（纽约伊萨卡）的牛奶质量改进计划进行了一项关于缺陷牛奶判断筛选和培训的初步研究。该研究包括康奈尔大学社区的 37 名工作人员和学生，他们使用常见气味和基本味觉的预筛选，然后进行统一培训，选择、初步培训和重新培训无风味高温短时间液态奶的缺陷评判员。所有缺陷属性的初始培训后，除了水果味/发酵味外，正确识别缺陷属性的能力均显著提高。然而，在重新培训后，仅在 2 个缺陷属性上观察到显著提高：煮熟味和牛奶纸盒味。这些结果表明，初始培训对于小组成员正确识别液态奶缺陷属性非常重要，但随后的再培训应针对特定属性进行。本研究为乳制品行业利益相关者提供了一个资源，用于开发相关且有效的液态奶缺陷判断小组培训方法。
